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An Asymptotic Theory for Estimating Beta-Pricing Models Using Cross-Sectional Regression


  • Ravi Jagannathan

    (Kellogg Graduate School of Management, Northwestern University and Carlson School of Management, University of Minnesota,)

  • Zhenyu Wang

    (Graduate School of Business, Columbia University)


Without the assumption of conditional homoskedasticity, a general asymptotic distribution theory for the two-stage cross-sectional regression method shows that the standard errors produced by the Fama-MacBeth procedure do not necessarily overstate the precision of the risk premium estimates. When factors are misspecified, estimators for risk premiums can be biased, and the "t"-value of a premium may converge to infinity in probability even when the true premium is zero. However, when a beta-pricing model is misspecified, the "t"-values for firm characteristics generally converge to infinity in probability, which supports the use of firm characteristics in cross-sectional regressions for detecting model misspecification. Copyright The American Finance Association 1998.

Suggested Citation

  • Ravi Jagannathan & Zhenyu Wang, 1998. "An Asymptotic Theory for Estimating Beta-Pricing Models Using Cross-Sectional Regression," Journal of Finance, American Finance Association, vol. 53(4), pages 1285-1309, August.
  • Handle: RePEc:bla:jfinan:v:53:y:1998:i:4:p:1285-1309

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